docs: def getTable(self, columns=None, table=None, network = "current", namespace='default', verbose=VERBOSE):
          """
          Gets tables from cytoscape.
  
          :param table: table to retrieve eg. node
          :param columns: columns to retrieve in list format
          :param network (string, optional): Specifies a network by name, or by
              SUID if the prefix SUID: is used. The keyword CURRENT, or a blank
              value can also be used to specify the current network.
          :param namespace (string, optional): Node, Edge, and Network objects support
              the default, local, and hidden namespaces. Root networks also support the
              shared namespace. Custom namespaces may be specified by Apps.
  
          :returns: a pandas dataframe
          """
  
          u=self.__url 
          host=u.split("//")[1].split(":")[0]
          port=u.split(":")[2].split("/")[0]
          version=u.split(":")[2].split("/")[1]
  
          if type(network) != int:
              network=check_network(self,network,verbose=verbose)
              PARAMS=set_param(["columnList","namespace","network"],["SUID",namespace,network])
              network=api(namespace="network", command="get attribute",PARAMS=PARAMS, host=host,port=str(port),version=version)
              network=network[0]["SUID"]
  
          df=pd.DataFrame()
          def target(column):
              URL="http://"+str(host)+":"+str(port)+"/v1/networks/"+str(network)+"/tables/"+namespace+table+"/columns/"+column
              if verbose:
                  print("'"+URL+"'")
                  sys.stdout.flush()
              response = urllib2.urlopen(URL)
              response = response.read()
              colA=json.loads(response)
  
              col=pd.DataFrame()    
              colHeader=colA["name"]
              colValues=colA["values"]
              col[colHeader]=colValues
              return col
  
          ncols=["name"]
          for c in columns:
              ncols.append(c.replace(" ","%20") )
          for c in ncols:
              try:
                  col=target(c)
                  df=pd.concat([df,col],axis=1)
              except:
                  print("Could not find "+c)
                  sys.stdout.flush()
  
          df.index=df["name"].tolist()
          df=df.drop(["name"],axis=1)
          return df